Advances in Predictive Models for Single-cell and Regulatory Genomics

Explore cutting-edge developments in predictive modeling for single-cell and regulatory genomics in this comprehensive lecture by Christina Leslie. Delve into the latest techniques and approaches used to analyze complex genomic data at the single-cell level. Learn how these advanced models are revolutionizing our understanding of gene regulation and cellular processes. Gain insights into the application of machine learning and statistical methods in genomics research. Discover how these predictive models are enhancing our ability to interpret large-scale genomic datasets and their potential impact on fields such as cancer research and personalized medicine. This talk is part of the "Theoretical Approaches in Cancer Progression and Treatment" program organized by the International Centre for Theoretical Sciences, offering a unique opportunity to understand the intersection of computational biology, genomics, and cancer research.